## Parsed with column specification:
## cols(
## date = col_date(format = ""),
## sum_mts_swe_m3 = col_double()
## )
##
## Call:
## lm(formula = mid_sj_spi$spi ~ mid_sj_spi$date)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.10335 -0.58415 0.02294 0.67057 2.42082
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.015e-01 1.359e-01 3.690 0.000251 ***
## mid_sj_spi$date -4.518e-05 1.152e-05 -3.921 0.000102 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9857 on 454 degrees of freedom
## Multiple R-squared: 0.03276, Adjusted R-squared: 0.03063
## F-statistic: 15.38 on 1 and 454 DF, p-value: 0.0001017
## TableGrob (2 x 2) "arrange": 4 grobs
## z cells name grob
## 1 1 (1-1,1-1) arrange gtable[layout]
## 2 2 (1-1,2-2) arrange gtable[layout]
## 3 3 (2-2,1-1) arrange gtable[layout]
## 4 4 (2-2,2-2) arrange gtable[layout]
## waterYear watershed spi swe_anom drought
## 1 2006 middle_sj -1.479390 -0.9098490 warning
## 2 2012 middle_sj -1.574148 -0.1368591 emergency
## 3 2018 middle_sj -2.028572 -0.9364887 emergency
##
## Call:
## lm(formula = chaco_spi$spi ~ chaco_spi$date)
##
## Residuals:
## Min 1Q Median 3Q Max
## -3.5627 -0.6231 0.0548 0.6595 2.3534
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 6.260e-01 1.346e-01 4.651 4.35e-06 ***
## chaco_spi$date -5.639e-05 1.141e-05 -4.942 1.09e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9764 on 454 degrees of freedom
## Multiple R-squared: 0.05105, Adjusted R-squared: 0.04896
## F-statistic: 24.42 on 1 and 454 DF, p-value: 1.089e-06
## TableGrob (2 x 2) "arrange": 4 grobs
## z cells name grob
## 1 1 (1-1,1-1) arrange gtable[layout]
## 2 2 (1-1,2-2) arrange gtable[layout]
## 3 3 (2-2,1-1) arrange gtable[layout]
## 4 4 (2-2,2-2) arrange gtable[layout]
- drought emergencies in 2006 and 2018
## waterYear watershed spi swe_anom drought
## 1 2006 chaco -1.663954 -0.90984896 emergency
## 2 2011 chaco -1.052243 -0.08834293 warning
## 3 2012 chaco -1.321458 -0.13685911 warning
## 4 2014 chaco -1.105010 -0.67909787 warning
## 5 2018 chaco -2.226117 -0.93648871 emergency
## TableGrob (2 x 2) "arrange": 4 grobs
## z cells name grob
## 1 1 (1-1,1-1) arrange gtable[layout]
## 2 2 (1-1,2-2) arrange gtable[layout]
## 3 3 (2-2,1-1) arrange gtable[layout]
## 4 4 (2-2,2-2) arrange gtable[layout]
## waterYear watershed spi swe_anom drought
## 1 2006 upper_puerco -1.627618 -0.9098490 emergency
## 2 2012 upper_puerco -1.464829 -0.1368591 warning
## 3 2013 upper_puerco -1.008209 0.3904031 warning
## 4 2018 upper_puerco -1.545492 -0.9364887 emergency
##
## Call:
## lm(formula = chinle_spi$spi ~ chinle_spi$date)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.55771 -0.44516 -0.02485 0.47069 1.39207
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.175e+00 8.549e-02 25.45 <2e-16 ***
## chinle_spi$date -1.961e-04 7.248e-06 -27.05 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6202 on 454 degrees of freedom
## Multiple R-squared: 0.6171, Adjusted R-squared: 0.6163
## F-statistic: 731.8 on 1 and 454 DF, p-value: < 2.2e-16
## TableGrob (2 x 2) "arrange": 4 grobs
## z cells name grob
## 1 1 (1-1,1-1) arrange gtable[layout]
## 2 2 (1-1,2-2) arrange gtable[layout]
## 3 3 (2-2,1-1) arrange gtable[layout]
## 4 4 (2-2,2-2) arrange gtable[layout]
plot_spi_drought_level(chinle_spi,
month = c(4),
region_time = "Navajo Nation March, April, May 6 month")
plot_spi_drought_level(chinle_spi,
month = all_months,
region_time = "Navajo Nation March, April, May 6 month",
years = "all")
## waterYear watershed spi swe_anom drought
## 1 2006 chinle -1.600052 -0.90984896 emergency
## 2 2007 chinle -1.314274 -0.85620097 warning
## 3 2009 chinle -1.094717 -0.14640716 warning
## 4 2011 chinle -1.232336 -0.08834293 warning
## 5 2012 chinle -1.600052 -0.13685911 emergency
## 6 2013 chinle -1.172496 0.39040309 warning
## 7 2014 chinle -1.377450 -0.67909787 warning
## 8 2016 chinle -1.019086 0.04659200 warning
## 9 2018 chinle -1.923309 -0.93648871 emergency
## watershed april_negative april_positive april_total
## 1 Middle San Juan 0.7 0.8333333 0.750
## 2 Chaco 0.7 0.5000000 0.625
## 3 Upper Puerco 0.8 0.6666667 0.750
## 4 Chinle 0.8 0.0000000 0.500